论大学物理实验体系建设与教学改革

传统的物理实验是按普通物理、电子线路和近代物理等内容进行划分，这种体系突出了学科的系统性，但忽视了学科之间的兼容互补性，各学科相互独立，限制了学生跨学科思维能力和创新能力的培养，建立现代物理实验教学新体系是大学物理实验教学改革的必然趋势．新的物理实验体系应依照训练层次，划分为引导性实验、基本实验、综合性实验、设计性实验、研究性实验．并需要注重时代性和先进性，改革和更新大学物理实验教学内容，改革实验教学与管理模式，形成新的运行机制，从而达到学生素质和能力的提高．     

基于互联网的物理专业实验教学改革与实践

互联网的普及和应用大幅改变了教师的课堂教学模式和学生的学习模式。本文首先介绍了物理专业实验课程的现状和在当前互联网普及应用背景下改革的必要性。然后重点阐述了基于互联网的专业物理实验课程的教学改革方案和实施方法。最后对教学改革的尝试所取得的效果和意义进行总结。     

光信息科学与技术专业的教学改革——双语教学

分析了光信息科学与技术专业的特点,探讨了该专业双语教学改革的特点和提高双语教学效果的方法,为专业发展提出了思路。     

Is the new ECTS system better than the traditional one? An application to the ECTS pilot-project at the University Pablo de Olavide

At the meeting of the joint Bologna Declaration, EU representatives agreed on the establishment of a common European Higher Education Area by 2010. Since then, several universities have implemented pilot projects, although no formal research has been carried out to analyse their results. In this study, we analysed one of these pilot-projects with two objectives. First, we examined the performance of the new system as compared to that of the traditional system. We used a procedure based on a modified model of Data Envelopment Analysis that is able to distinguish students’ efficiency (managerial efficiency) from efficiency based on the educational programme used (programme efficiency). Then we analysed whether the different systems perform differently for different types of students.     

奥尔堡PBL模式对提升有机波谱分析教学效果的启示

概述了有机波谱分析课程教学中存在的主要问题,介绍了奥尔堡PBL模式的主要特点和优势,分析了将奥尔堡PBL模式用于有机波谱分析课程教学的必要性和可行性,并从课时分配、教学内容、教学方式和考核方式等4方面提出了教学改革方案,旨在提高教学效果。     

高等数学课程改革的新探索

讨论大专高等数学的教学改革,主要介绍我们对此问题的理解和所做的改革试验.试验围绕如何使微机在大专高等数学教学中发挥作用、编写新的教材、提倡建构式教学法等三方面展开.教学实践表明,我们的改革试验是比较有成效的.     

两部美国大学物理教材对我们教学改革的启示

介绍了美国两部大学物理教材的特点，分析了美国教材在教学内容、教学方法、教学手段现代化方面的特色，为我们的教学改革提供一些可供借鉴的经验。     

《微分方程数值解》课程教学改革与实践

针对一般本科院校的教学实际,研讨《微分方程数值解》课程教学改革的一些体会,主要包括教学定位的确定、课程教学内容的优化、教学方法的改革以及教学手段的更新等问题.     

启发式教学在仪器分析实验教学中的应用

以恒电流电解法测铜为例,介绍了启发式教学在仪器分析实验教学中的应用.通过启发式教学,引导学生学以致用,充分调动了学生的学习积极性,培养了学生独立解决问题的能力,在巩固已学知识的同时,提高了实验教学质量.     

Gaining insight into student satisfaction using comprehensible data mining techniques

As a consequence of the heightened competition on the education market, the management of educational institutions often attempts to collect information on what drives student satisfaction by e.g. organizing large scale surveys amongst the student population. Until now, this source of potentially very valuable information remains largely untapped. In this study, we address this issue by investigating the applicability of different data mining techniques to identify the main drivers of student satisfaction in two business education institutions. In the end, the resulting models are to be used by the management to support the strategic decision making process. Hence, the aspect of model comprehensibility is considered to be at least equally important as model performance. It is found that data mining techniques are able to select a surprisingly small number of constructs that require attention in order to manage student satisfaction.